Summary
Ben Lerner is a Senior Machine Learning Engineer in New York with 11 years of experience building production ML systems across consumer tech, logistics, and automotive telematics. He has driven large-scale data pipelines and feature engineering at Snap and DoorDash, built a 4x-faster feature store and fleet risk models at Viaduct that surfaced recalls months before OEMs, and now focuses on personalization at Meta AI. Comfortable across Spark, Airflow, Beam, Postgres and experimentation backends, he combines strong software engineering rigor with applied ML evaluation and monitoring. He has research-oriented interests in alignment and sparse autoencoders, having participated in AI safety work and published with Apollo Research. A founder-level engineer (co-founder of Espresso Computing) who started in product-focused roles at Columbia and startups, he blends hands-on implementation with systems thinking and measurable business impact.
11 years of coding experience
8 years of employment as a software developer
Bachelor's Degree Computer Science, Bachelor's Degree Computer Science at Columbia University
Alignment, Alignment at AI Safety Fundamentals
English, Japanese